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Modelling the loss and retention of contacts in social networks: The role of dyad-level heterogeneity and tie strength

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  • Calastri, Chiara
  • Hess, Stephane
  • Daly, Andrew
  • Carrasco, Juan Antonio
  • Choudhury, Charisma

Abstract

Social networks have attracted attention in different fields of research in recent years and choice modellers have engaged with their analysis by looking at the role that social networks play in shaping decisions across a variety of contexts. The incorporation of the social dimension in choice models creates the need for understanding how social networks evolve over time and in particular which social contacts (alters) are retained over time by an individual (ego). Existing work fails to capture the full extent of ego-level and ego-alter level heterogeneity in these processes. We propose the use of a hybrid model framework which is based on the notion of latent strength of relationship. The resulting model allows for heterogeneity in the latent strength both across individuals and across their different relationships. In addition, we allow for heterogeneity not linked to the latent strength concept. We demonstrate the benefits of the approach using data from Chile, showing the presence of extensive variations in retention of social contacts and in strength of relationship both at the ego and ego-alter level, only some of which can be linked to observed characteristics.

Suggested Citation

  • Calastri, Chiara & Hess, Stephane & Daly, Andrew & Carrasco, Juan Antonio & Choudhury, Charisma, 2018. "Modelling the loss and retention of contacts in social networks: The role of dyad-level heterogeneity and tie strength," Journal of choice modelling, Elsevier, vol. 29(C), pages 63-77.
    • Handle: RePEc:eee:eejocm:v:29:y:2018:i:c:p:63-77
    DOI: 10.1016/j.jocm.2018.03.004
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    1. Sharmeen, Fariya & Arentze, Theo & Timmermans, Harry, 2014. "An analysis of the dynamics of activity and travel needs in response to social network evolution and life-cycle events: A structural equation model," Transportation Research Part A: Policy and Practice, Elsevier, vol. 59(C), pages 159-171.
    2. Chiou, Lesley & Walker, Joan L., 2007. "Masking identification of discrete choice models under simulation methods," Journal of Econometrics, Elsevier, vol. 141(2), pages 683-703, December.
    3. Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
    4. Walker, Joan L. & Ehlers, Emily & Banerjee, Ipsita & Dugundji, Elenna R., 2011. "Correcting for endogeneity in behavioral choice models with social influence variables," Transportation Research Part A: Policy and Practice, Elsevier, vol. 45(4), pages 362-374, May.
    5. Cherchi, Elisabetta & Guevara, Cristian Angelo, 2012. "A Monte Carlo experiment to analyze the curse of dimensionality in estimating random coefficients models with a full variance–covariance matrix," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 321-332.
    6. Dekker, Thijs & Hess, Stephane & Brouwer, Roy & Hofkes, Marjan, 2016. "Decision uncertainty in multi-attribute stated preference studies," Resource and Energy Economics, Elsevier, vol. 43(C), pages 57-73.
    7. Calastri, Chiara & Hess, Stephane & Daly, Andrew & Carrasco, Juan Antonio, 2017. "Does the social context help with understanding and predicting the choice of activity type and duration? An application of the Multiple Discrete-Continuous Nested Extreme Value model to activity diary," Transportation Research Part A: Policy and Practice, Elsevier, vol. 104(C), pages 1-20.
    8. Antonio Páez & Darren M Scott, 2007. "Social Influence on Travel Behavior: A Simulation Example of the Decision to Telecommute," Environment and Planning A, , vol. 39(3), pages 647-665, March.
    9. Juan Antonio Carrasco & Beatriz Cid-Aguayo, 2012. "Network Capital, Social Networks, and Travel: An Empirical Illustration from Concepción, Chile," Environment and Planning A, , vol. 44(5), pages 1066-1084, May.
    10. Sadri, Arif Mohaimin & Ukkusuri, Satish V. & Gladwin, Hugh, 2017. "Modeling joint evacuation decisions in social networks: The case of Hurricane Sandy," Journal of choice modelling, Elsevier, vol. 25(C), pages 50-60.
    11. Juan Antonio Carrasco & Bernie Hogan & Barry Wellman & Eric J Miller, 2008. "Collecting Social Network Data to Study Social Activity-Travel Behavior: An Egocentric Approach," Environment and Planning B, , vol. 35(6), pages 961-980, December.
    12. Fariya Sharmeen & Theo Arentze & Harry Timmermans, 2015. "Predicting the evolution of social networks with life cycle events," Transportation, Springer, vol. 42(5), pages 733-751, September.
    13. Maness, Michael & Cirillo, Cinzia & Dugundji, Elenna R., 2015. "Generalized behavioral framework for choice models of social influence: Behavioral and data concerns in travel behavior," Journal of Transport Geography, Elsevier, vol. 46(C), pages 137-150.
    14. Hess, Stephane & Train, Kenneth E., 2011. "Recovery of inter- and intra-personal heterogeneity using mixed logit models," Transportation Research Part B: Methodological, Elsevier, vol. 45(7), pages 973-990, August.
    15. Almquist, Zack W. & Butts, Carter T., 2013. "Dynamic Network Logistic Regression: A Logistic Choice Analysis of Inter- and Intra-Group Blog Citation Dynamics in the 2004 US Presidential Election," Political Analysis, Cambridge University Press, vol. 21(4), pages 430-448.
    16. Hess, Stephane & Rose, John M., 2009. "Allowing for intra-respondent variations in coefficients estimated on repeated choice data," Transportation Research Part B: Methodological, Elsevier, vol. 43(6), pages 708-719, July.
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